@n8n/n8n-nodes-langchain
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272 lines • 9.72 kB
JavaScript
;
var __defProp = Object.defineProperty;
var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
var __getOwnPropNames = Object.getOwnPropertyNames;
var __hasOwnProp = Object.prototype.hasOwnProperty;
var __export = (target, all) => {
for (var name in all)
__defProp(target, name, { get: all[name], enumerable: true });
};
var __copyProps = (to, from, except, desc) => {
if (from && typeof from === "object" || typeof from === "function") {
for (let key of __getOwnPropNames(from))
if (!__hasOwnProp.call(to, key) && key !== except)
__defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
}
return to;
};
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);
var LmChatAwsBedrock_node_exports = {};
__export(LmChatAwsBedrock_node_exports, {
LmChatAwsBedrock: () => LmChatAwsBedrock
});
module.exports = __toCommonJS(LmChatAwsBedrock_node_exports);
var import_client_bedrock_runtime = require("@aws-sdk/client-bedrock-runtime");
var import_aws = require("@langchain/aws");
var import_node_http_handler = require("@smithy/node-http-handler");
var import_httpProxyAgent = require("../../../utils/httpProxyAgent");
var import_sharedFields = require("../../../utils/sharedFields");
var import_n8n_workflow = require("n8n-workflow");
var import_n8nLlmFailedAttemptHandler = require("../n8nLlmFailedAttemptHandler");
var import_N8nLlmTracing = require("../N8nLlmTracing");
class LmChatAwsBedrock {
constructor() {
this.description = {
displayName: "AWS Bedrock Chat Model",
name: "lmChatAwsBedrock",
icon: "file:bedrock.svg",
group: ["transform"],
version: [1, 1.1],
description: "Language Model AWS Bedrock",
defaults: {
name: "AWS Bedrock Chat Model"
},
codex: {
categories: ["AI"],
subcategories: {
AI: ["Language Models", "Root Nodes"],
"Language Models": ["Chat Models (Recommended)"]
},
resources: {
primaryDocumentation: [
{
url: "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatawsbedrock/"
}
]
}
},
inputs: [],
outputs: [import_n8n_workflow.NodeConnectionTypes.AiLanguageModel],
outputNames: ["Model"],
credentials: [
{
name: "aws",
required: true
}
],
requestDefaults: {
ignoreHttpStatusErrors: true,
baseURL: '=https://bedrock.{{$credentials?.region ?? "eu-central-1"}}.amazonaws.com'
},
properties: [
(0, import_sharedFields.getConnectionHintNoticeField)([import_n8n_workflow.NodeConnectionTypes.AiChain, import_n8n_workflow.NodeConnectionTypes.AiChain]),
{
displayName: "Model Source",
name: "modelSource",
type: "options",
displayOptions: {
show: {
"@version": [{ _cnd: { gte: 1.1 } }]
}
},
options: [
{
name: "On-Demand Models",
value: "onDemand",
description: "Standard foundation models with on-demand pricing"
},
{
name: "Inference Profiles",
value: "inferenceProfile",
description: "Cross-region inference profiles (required for models like Claude Sonnet 4 and others)"
}
],
default: "onDemand",
description: "Choose between on-demand foundation models or inference profiles"
},
{
displayName: "Model",
name: "model",
type: "options",
allowArbitraryValues: true,
// Hide issues when model name is specified in the expression and does not match any of the options
description: 'The model which will generate the completion. <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/foundation-models.html">Learn more</a>.',
displayOptions: {
hide: {
modelSource: ["inferenceProfile"]
}
},
typeOptions: {
loadOptionsDependsOn: ["modelSource"],
loadOptions: {
routing: {
request: {
method: "GET",
url: "/foundation-models?&byOutputModality=TEXT&byInferenceType=ON_DEMAND"
},
output: {
postReceive: [
{
type: "rootProperty",
properties: {
property: "modelSummaries"
}
},
{
type: "setKeyValue",
properties: {
name: "={{$responseItem.modelName}}",
description: "={{$responseItem.modelArn}}",
value: "={{$responseItem.modelId}}"
}
},
{
type: "sort",
properties: {
key: "name"
}
}
]
}
}
}
},
routing: {
send: {
type: "body",
property: "model"
}
},
default: ""
},
{
displayName: "Model",
name: "model",
type: "options",
allowArbitraryValues: true,
description: 'The inference profile which will generate the completion. <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-use.html">Learn more</a>.',
displayOptions: {
show: {
modelSource: ["inferenceProfile"]
}
},
typeOptions: {
loadOptionsDependsOn: ["modelSource"],
loadOptions: {
routing: {
request: {
method: "GET",
url: "/inference-profiles?maxResults=1000"
},
output: {
postReceive: [
{
type: "rootProperty",
properties: {
property: "inferenceProfileSummaries"
}
},
{
type: "setKeyValue",
properties: {
name: "={{$responseItem.inferenceProfileName}}",
description: "={{$responseItem.description || $responseItem.inferenceProfileArn}}",
value: "={{$responseItem.inferenceProfileId}}"
}
},
{
type: "sort",
properties: {
key: "name"
}
}
]
}
}
}
},
routing: {
send: {
type: "body",
property: "model"
}
},
default: ""
},
{
displayName: "Options",
name: "options",
placeholder: "Add Option",
description: "Additional options to add",
type: "collection",
default: {},
options: [
{
displayName: "Maximum Number of Tokens",
name: "maxTokensToSample",
default: 2e3,
description: "The maximum number of tokens to generate in the completion",
type: "number"
},
{
displayName: "Sampling Temperature",
name: "temperature",
default: 0.7,
typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
description: "Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.",
type: "number"
}
]
}
]
};
}
async supplyData(itemIndex) {
const credentials = await this.getCredentials("aws");
const modelName = this.getNodeParameter("model", itemIndex);
const options = this.getNodeParameter("options", itemIndex, {});
const proxyAgent = (0, import_httpProxyAgent.getNodeProxyAgent)();
const clientConfig = {
region: credentials.region,
credentials: {
secretAccessKey: credentials.secretAccessKey,
accessKeyId: credentials.accessKeyId,
...credentials.sessionToken && { sessionToken: credentials.sessionToken }
}
};
if (proxyAgent) {
clientConfig.requestHandler = new import_node_http_handler.NodeHttpHandler({
httpAgent: proxyAgent,
httpsAgent: proxyAgent
});
}
const client = new import_client_bedrock_runtime.BedrockRuntimeClient(clientConfig);
const model = new import_aws.ChatBedrockConverse({
client,
model: modelName,
region: credentials.region,
temperature: options.temperature,
maxTokens: options.maxTokensToSample,
callbacks: [new import_N8nLlmTracing.N8nLlmTracing(this)],
onFailedAttempt: (0, import_n8nLlmFailedAttemptHandler.makeN8nLlmFailedAttemptHandler)(this)
});
return {
response: model
};
}
}
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
LmChatAwsBedrock
});
//# sourceMappingURL=LmChatAwsBedrock.node.js.map